Cargando…

Research on Cold Start of Proton-Exchange Membrane Fuel Cells Based on Model Predictive Control

The cold start of fuel cells limits their wide application. Since the water produced by fuel cells takes up more space when it freezes, it may affect the internal structure of the stack, causing collapse and densification of the pores inside the catalytic layer. This paper mainly analyzes the influe...

Descripción completa

Detalles Bibliográficos
Autores principales: Xiong, Shusheng, Wu, Zhankuan, Jiang, Qi, Zhao, Jiahao, Wang, Tianxin, Deng, Jianan, Huang, Heqing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9967530/
https://www.ncbi.nlm.nih.gov/pubmed/36837687
http://dx.doi.org/10.3390/membranes13020184
_version_ 1784897287719223296
author Xiong, Shusheng
Wu, Zhankuan
Jiang, Qi
Zhao, Jiahao
Wang, Tianxin
Deng, Jianan
Huang, Heqing
author_facet Xiong, Shusheng
Wu, Zhankuan
Jiang, Qi
Zhao, Jiahao
Wang, Tianxin
Deng, Jianan
Huang, Heqing
author_sort Xiong, Shusheng
collection PubMed
description The cold start of fuel cells limits their wide application. Since the water produced by fuel cells takes up more space when it freezes, it may affect the internal structure of the stack, causing collapse and densification of the pores inside the catalytic layer. This paper mainly analyzes the influence of different startup strategies on the stack cold start, focusing on the change in the stack temperature and the ice volume fraction of the catalytic layer. When designing a startup strategy, it is important to focus not only on the optimization of the startup time, but also on the principle of minimizing the damage to the stack. A lumped parameter cold-start model was constructed, which was experimentally verified to have a maximum error of 8.9%. On this basis, a model predictive control (MPC) algorithm was used to control the starting current. The MPC cold-start strategy reached the freezing point at 17 s when the startup temperature was −10 °C, which is faster than other startup strategies. Additionally, the time to ice production was controlled to about 20 s. Compared with the potentiostatic strategy and maximum power strategy, MPC is optimal and still has great potential for further optimization.
format Online
Article
Text
id pubmed-9967530
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-99675302023-02-27 Research on Cold Start of Proton-Exchange Membrane Fuel Cells Based on Model Predictive Control Xiong, Shusheng Wu, Zhankuan Jiang, Qi Zhao, Jiahao Wang, Tianxin Deng, Jianan Huang, Heqing Membranes (Basel) Article The cold start of fuel cells limits their wide application. Since the water produced by fuel cells takes up more space when it freezes, it may affect the internal structure of the stack, causing collapse and densification of the pores inside the catalytic layer. This paper mainly analyzes the influence of different startup strategies on the stack cold start, focusing on the change in the stack temperature and the ice volume fraction of the catalytic layer. When designing a startup strategy, it is important to focus not only on the optimization of the startup time, but also on the principle of minimizing the damage to the stack. A lumped parameter cold-start model was constructed, which was experimentally verified to have a maximum error of 8.9%. On this basis, a model predictive control (MPC) algorithm was used to control the starting current. The MPC cold-start strategy reached the freezing point at 17 s when the startup temperature was −10 °C, which is faster than other startup strategies. Additionally, the time to ice production was controlled to about 20 s. Compared with the potentiostatic strategy and maximum power strategy, MPC is optimal and still has great potential for further optimization. MDPI 2023-02-02 /pmc/articles/PMC9967530/ /pubmed/36837687 http://dx.doi.org/10.3390/membranes13020184 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Xiong, Shusheng
Wu, Zhankuan
Jiang, Qi
Zhao, Jiahao
Wang, Tianxin
Deng, Jianan
Huang, Heqing
Research on Cold Start of Proton-Exchange Membrane Fuel Cells Based on Model Predictive Control
title Research on Cold Start of Proton-Exchange Membrane Fuel Cells Based on Model Predictive Control
title_full Research on Cold Start of Proton-Exchange Membrane Fuel Cells Based on Model Predictive Control
title_fullStr Research on Cold Start of Proton-Exchange Membrane Fuel Cells Based on Model Predictive Control
title_full_unstemmed Research on Cold Start of Proton-Exchange Membrane Fuel Cells Based on Model Predictive Control
title_short Research on Cold Start of Proton-Exchange Membrane Fuel Cells Based on Model Predictive Control
title_sort research on cold start of proton-exchange membrane fuel cells based on model predictive control
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9967530/
https://www.ncbi.nlm.nih.gov/pubmed/36837687
http://dx.doi.org/10.3390/membranes13020184
work_keys_str_mv AT xiongshusheng researchoncoldstartofprotonexchangemembranefuelcellsbasedonmodelpredictivecontrol
AT wuzhankuan researchoncoldstartofprotonexchangemembranefuelcellsbasedonmodelpredictivecontrol
AT jiangqi researchoncoldstartofprotonexchangemembranefuelcellsbasedonmodelpredictivecontrol
AT zhaojiahao researchoncoldstartofprotonexchangemembranefuelcellsbasedonmodelpredictivecontrol
AT wangtianxin researchoncoldstartofprotonexchangemembranefuelcellsbasedonmodelpredictivecontrol
AT dengjianan researchoncoldstartofprotonexchangemembranefuelcellsbasedonmodelpredictivecontrol
AT huangheqing researchoncoldstartofprotonexchangemembranefuelcellsbasedonmodelpredictivecontrol